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Updated: Aug 19, 2026

Assessing Cerebral Autoregulation via Oscillatory Lower Body Negative Pressure and Projection Pursuit Regression
Published on: December 10, 2014
Assessment of cerebral autoregulation from ectopic heartbeats
Penelope J Eames1, John F Potter, Ronney B Panerai
1University of Leicester Divisions of Medicine for the Elderly, Glenfield Hospital, Leicester LE3 9QP, UK.
Abstract:
Transfer function analysis of spontaneous fluctuations in BP (blood pressure) and CBFV (cerebral blood flow velocity) has been widely used to study dynamic CA (cerebral autoregulation). The inverse Fourier transform and its integral, giving the impulse and step responses, have been used to gain perspective of the state of dynamic CA from the frequency and time domains respectively. The occurrence of ectopic heartbeats in the data has usually been treated as an artefact. Data containing multiple ectopic heartbeats were selected from a data set compiled for an acute stroke study which also included bilateral middle CBFV, concurrent surface ECG and non-invasive beat-to-beat BP recordings. Transfer function analysis and impulse and step responses were calculated from these data by (i) retaining ectopic heartbeats, (ii) after removal of ectopic heartbeats and replacement by linear interpolation, and (iii) using a narrow window of data surrounding selected ectopic heartbeats. Coherent averaging of the raw data of the selected ectopic heartbeats also allowed direct visualization of the relationship between BP changes and CBFV. The impulse and step responses were similar in shape whether or not ectopic heartbeats had been removed and showed characteristics of active dynamic CA. Removal of ectopic heartbeats from the CBFV and BP tracings, by linear interpolation or other methods, is not necessary to provide reliable estimates of dynamic autoregulation in subjects with ectopic heartbeat rates of up to eight per min. Additionally, impulse-like disturbances of BP induced by single-beat ectopic heartbeats provide enough information to characterize the autoregulatory response of the subject in agreement with more traditional methods of dynamic autoregulation assessment.
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